Richard Sharp
About Richard Sharp
Richard Sharp is a Principal Data Scientist with extensive experience in data science and machine learning. He has worked at notable organizations including Microsoft, Globys Inc, and Carnegie Mellon University, and holds a Ph.D. in Computational and Applied Mathematics from Princeton University.
Work at Cambridge Mobile Telematics
Richard Sharp has been serving as a Principal Data Scientist at Cambridge Mobile Telematics since 2019. In this role, he applies his expertise in data science to enhance telematics solutions. His work focuses on analyzing large datasets to improve driving behavior insights and insurance risk assessments. Sharp's contributions are integral to the company's mission of making roads safer through data-driven technologies.
Previous Experience at Microsoft
Before joining Cambridge Mobile Telematics, Richard Sharp worked at Microsoft as a Program Manager from 2011 to 2014. During his tenure in Redmond, WA, he was involved in various projects that required coordination between technical teams and stakeholders. His role emphasized project management and the implementation of software solutions, contributing to the development of innovative products.
Experience at Globys Inc
Richard Sharp was employed at Globys Inc as a Machine Learning Scientist from 2014 to 2016. Based in Seattle, he focused on leveraging machine learning techniques to enhance business solutions. His work involved developing algorithms that improved data analysis and customer insights, supporting the company’s objectives in the telecommunications sector.
Academic Background
Richard Sharp earned his Doctor of Philosophy (Ph.D.) in Computational and Applied Mathematics from Princeton University, where he studied from 2001 to 2005. Prior to that, he completed a Bachelor of Arts in Mathematics at Northwestern University from 1997 to 2001. His academic background provided a strong foundation in quantitative analysis and problem-solving, which he has applied throughout his career.
Postdoctoral Experience at Carnegie Mellon University
Richard Sharp served as a Postdoctoral Associate at Carnegie Mellon University from 2007 to 2010. During this period in Pittsburgh, PA, he engaged in research that contributed to advancements in data science and applied mathematics. His postdoctoral work allowed him to deepen his expertise and collaborate with leading researchers in the field.